MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 2
Home: Own 
Employment: Self-employed full time
Occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Exercise 
Devices used daily: Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini;Meta Llama 2 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Generate art;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Work;Entertainment;Learning;Creative or artistic 
Prompt 1: Thinking about the interest rates that people pay to borrow money, such as mortgage rates, what do you expect the average interest rate to be over the next 12 months? Just a guess
Prompt 2: in eq2, how can i get my level 10 character in darklight wood to my friends character in kunark?
Prompt 3: i have an old wooden door, the inner door of a set of 2 where the outer door is a storm door. this inner wooden door no longer sits flush with the door frame in the top left corner. at the peak of the top left corner, it sticks out nearly 1/2 inch. is there any way i can fix this or do i need to get a new door?
Prompt 4: is there a way to make a pc play 2 seperate audio sources to 2 different sets of speakers?
Prompt 5: can you tell me if the tcl 43q651g tv supports VRR when hooked up to a rtx 4070?
Prompt 6: what is carbonic maceration, who is behind it, and what are semi-carbonic maceration and variations
Prompt 7: would i gain much by upgrading my Crucial Ballistix Sport LT 3200 MHz DDR4 DRAM 32gb?
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 3
Home: Other (Please specify) live with relatives
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Use social media 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Never
Gender: Female 
Age: 55-60
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Self-employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Do arts and crafts;Go to museums and galleries;Attend football matches;Watch sports;Other (Please specify) stargazing
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Rarely
LLMs used: Google Gemini 
LLM use cases: Translation 
Contexts of LLM use: Learning 
Prompt 1: weather
Prompt 2: sports
Prompt 3: translation 
Prompt 4: general knowledge
Prompt 5: top ten music 
Prompt 6: local events
Prompt 7: fact checking
Prompt 8: recipes
Prompt 9: directions
Prompt 10: recommendations  
Comments: no
Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: Black or African American 
Marital status: Divorced 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 8
Home: Rent 
Employment: Employed full time
Occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to hiphop and rap;Exercise;Use social media;Go to museums and galleries;Do arts and crafts;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Paraphrasing or finding synonyms;Digital content creation (e.g., creation of social media content);Generate art;Answering questions about general knowledge 
Contexts of LLM use: Creative or artistic;Personal;Technical;Learning 
Prompt 1: What tea is good for swollen lymph nodes
Prompt 2: What is the best bait to get rid of rats
Prompt 3: What kind of  tea is best for stomach aches.
Prompt 4: are schools going to be closed for possible snow day in Atlanta
Prompt 5: what foods are good to feed cats
Comments: No I don’t have any questions or comments about AI chatbots.
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Never
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Other (Please specify) Live with parents who own home
Employment: Not employed, but looking for work
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Exercise;Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Proofreading/Editing (e.g., grammar, spelling, structure improvements);Paraphrasing or finding synonyms;Writing (e.g., composing emails);Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Learning 
Prompt 1: What is the difference between HPD and BPD?
Prompt 2: Is a golden retriever or collie a better dog?
Prompt 3: What are the drones in New Jersey?
Prompt 4: What do you know about me?
Prompt 5: Analyze my resume and tell me what to improve on.
Prompt 6: Does this look like basal cell carcinoma?
Prompt 7: Based on what you know about me, what careers do you think I'd  be good at and why?
Prompt 8: What are the key differences between a nurse practitioner and physician's assistant?
Prompt 9: What should I feed my 64 year old diabetic type 2 father who just had a heart attack?
Prompt 10: How can I improve my vegetarian diet to get more iron?
Gender: Male 
Age: 18-24
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Attend football matches;Watch sports;Use social media;Exercise;Listen to hiphop and rap 
Devices used daily: Smartphone;Laptop;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Claude;Google Bard 
LLM use cases: Coding;Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Digital content creation (e.g., creation of social media content);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Analyze data;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Work;School/University;Personal;Creative or artistic;Technical;Learning 
Prompt 1: Can you help me create a professional summary for my LinkedIn profile?
Prompt 2: Explain the difference between UX and UI design in simple terms.
Prompt 3: How can I overcome the fear of posting my work on social media?
Prompt 4: What's the best way to prepare for a job interview in tech?
Prompt 5: What's the difference between machine learning and artificial intelligence?
Prompt 6: Suggest a weekly workout plan for building muscle at home.
Prompt 7: Explain the plot of Inception in a simple way.
Prompt 8: Explain how blockchain technology works.
Prompt 9: What are some effective strategies to stay productive while working from home?
Prompt 10: Can you recommend some good books for personal development?
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: Hispanic 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Self-employed part time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Exercise;Use social media;Go to museums and galleries 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: Snapchat My AI 
LLM use cases: Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Personal
Gender: Non-binary 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Other (Please Specify) Committed Relationship
First language: English 
Religion: Prefer not to say 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Prefer not to say
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to rock/indie music;Listen to hiphop and rap;Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Never
Gender: Male 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Retired
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Exercise;Attend football matches 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Sometimes
LLM use cases: Writing (e.g., composing emails)
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Doctorate or above
Mother's education: Doctorate or above
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to classical music;Exercise;Attend football matches 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Every day
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Translation 
Contexts of LLM use: Learning 
Prompt 1: Can you explain the theory of relativity in simple terms?
Prompt 2: What’s a good recipe for a vegan chocolate cake?
Prompt 3: Help me come up with a name for my new podcast about technology
Prompt 4: Can you summarize the plot of The Great Gatsby?
Prompt 5: Give me some ideas for a creative birthday gift for my friend.
Prompt 6: Could you write a short story based on the theme of time travel?
Prompt 7: What are the best ways to reduce stress in everyday life?
Prompt 8: Help me write a professional email asking for feedback on a project.
Prompt 9: How do I improve my productivity while working from home?
Prompt 10: What are some tips for studying effectively for a final exam?
Comments: none
Gender: Female 
Age: 60+
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Own 
Employment: Not employed, but looking for work
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Hobbies: Use social media;Other (Please specify) read, garden, tv, hike, birdwatch, nature watch
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Never
Gender: Female 
Age: 45-54
Nationality: United States
Marital status: Married 
First language: English;German 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to jazz;Go to gigs;Exercise 
Devices used daily: Smartphone;Laptop;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Claude;GitHub Copilot;Google Gemini;Jasper 
LLM use cases: Translation;Coding;Writing (e.g., composing emails);Solving math or logical problems;Generate art 
Contexts of LLM use: Learning;Work;Technical;Creative or artistic;Personal;Entertainment 
Prompt 1: which is the best alternative to deepfake which is user friendly interface
Prompt 2: How many justices serve on the United States Supreme Court?
Prompt 3: What is the highest yield I can get in an acre
Prompt 4: Which variety should I choose based on market demand
Prompt 5: How to use activated charcoal for stomach issues?
Prompt 6: How many tones of potatoes can I get in one acre 
Prompt 7: Digital Doppelganger
Prompt 8: how do they do? does Binance have such risks
Prompt 9: comparing microtopping and terrazzo for waterproofing
Gender: Male 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 9
Home: Own 
Employment: Not employed and not looking for work
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise;Use social media;Attend football matches;Watch sports;Other (Please specify) cinema, volunteering in the community, tennis, squash
Devices used daily: Laptop;Smartphone;Other desktop
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Never
Gender: Male 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 1
Home: Rent 
Employment: Not employed and not looking for work
Occupation: Prefer not to say
Mother's occupation: Homemaker
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to rock/indie music;Use social media;Watch sports 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Other (specify) I don't understand the meaning of don't use because of scarce performance. I have used all of these and continue to on an as needed or wanted basis
Frequency of LLM use: Sometimes
LLMs used: Google Gemini;ChatGPT;Meta Llama 2 
LLM use cases: Translation;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Digital content creation (e.g., creation of social media content);Generic chatbot conversation 
Contexts of LLM use: Entertainment;Learning;Personal
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Muslim 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Exercise;Attend football matches 
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Spell checker (i.e., correcting misspellings) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Character.AI 
LLM use cases: Translation;Writing (e.g., composing emails);Coding 
Contexts of LLM use: Work;Learning 
Prompt 1: How to code
Prompt 2: Correcting  errors
Prompt 3: How do you ensure data quality and accuracy in your analysis
Prompt 4: What are the key skills required to become a successful data analyst
Prompt 5: How do you approach data storytelling, and what strategies do you use to make insights actionable
Prompt 6: Can you explain the concept of correlation versus causation in data analysis
Prompt 7: What are some common data visualization best practices
Prompt 8: 8. How do you stay up-to-date with new tools, technologies, and methodologies in the field of data analysis
Prompt 9: What can I do differently as a data analyst
Prompt 10: How can I develop myself as the best data analyst
Comments: No comments
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 1
Home: Prefer not to say 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Answering questions about general knowledge 
Contexts of LLM use: Work 
Prompt 1: answering surveys
Comments: no
Gender: Male 
Age: 45-54
Nationality: United Kingdom
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Own 
Employment: Employed part time
Occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Mother's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Exercise;Use social media;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLM use cases: Brainstorming 
Contexts of LLM use: Personal 
Prompt 1: Tell me about Hanoi
Prompt 2: Tell me about Bangkok 
Prompt 3: Tell me about vang veing
Prompt 4: Tell me about Vietnam 
Prompt 5: Tell me about laos
Prompt 6: Tell me about thailand
Prompt 7: Tell me about cambodia
Prompt 8: Tell me about bangladesh
Prompt 9: Tell me about Burkina faso
Prompt 10: What countries are most scenic 
Comments: No
Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: Black or African American 
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Homemaker
Mother's occupation: Homemaker
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to hiphop and rap;Listen to rock/indie music;Exercise;Use social media 
Devices used daily: Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Answering questions about general knowledge 
Contexts of LLM use: Personal 
Prompt 1: A recipe for wonton soup?
Prompt 2: Ingredients for wonton soup 
Prompt 3: How much ground ginger equals 1 teaspoon of minced ginger 
Prompt 4: How is one garlic clove minced 
Prompt 5: Recipe for shrimp fried rice 
Prompt 6: I don’t have peas and carrots 
Prompt 7: What can I make with leftover barbacoa, tortilla chips and cheese 
Prompt 8: What can I make with barbacoa, tortilla chips, and cheese?
Prompt 9: How to cook whole green beans 
Prompt 10: How to make a frittata 
Comments: No.
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Prefer not to say
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Student
Occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort);Homemaker
Mother's occupation: Prefer not to say
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to hiphop and rap;Listen to rock/indie music;Exercise;Watch dance or ballet 
Devices used daily: Tablet;Smartphone;Laptop;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;Snapchat My AI;Character.AI 
LLM use cases: Generic chatbot conversation 
Contexts of LLM use: Entertainment 
Prompt 1: Hey Jerma985 how funny do you think you are? Give us a great joke!
Prompt 2: What are some tips on being funny like you?
Prompt 3: What if people really dont find me funny?
Prompt 4: Will you be here when I get back?
Gender: Female 
Age: 45-54
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Own 
Employment: Retired
Occupation: Prefer not to say
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information);Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;Other Pirr, erotic GPT writing.
LLM use cases: Brainstorming;Other (specify) erotic stimulation (Pirr)
Contexts of LLM use: Entertainment 
Prompt 1: It wrote an erotic story about the actor Dominic Monaghan.
Prompt 2: Erotic story about vampires
Prompt 3: erotic story about cowboys